Instructions to use swcrazyfan/TEFL-blogging-9K with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use swcrazyfan/TEFL-blogging-9K with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="swcrazyfan/TEFL-blogging-9K")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("swcrazyfan/TEFL-blogging-9K")
model = AutoModelForCausalLM.from_pretrained("swcrazyfan/TEFL-blogging-9K", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use swcrazyfan/TEFL-blogging-9K with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "swcrazyfan/TEFL-blogging-9K"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "swcrazyfan/TEFL-blogging-9K",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/swcrazyfan/TEFL-blogging-9K

SGLang

How to use swcrazyfan/TEFL-blogging-9K with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "swcrazyfan/TEFL-blogging-9K" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "swcrazyfan/TEFL-blogging-9K",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "swcrazyfan/TEFL-blogging-9K" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "swcrazyfan/TEFL-blogging-9K",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use swcrazyfan/TEFL-blogging-9K with Docker Model Runner:
```
docker model run hf.co/swcrazyfan/TEFL-blogging-9K
```

Model Description and Example Code?

by lazyDataScientist - opened Oct 3, 2022

Discussion

lazyDataScientist

Oct 3, 2022

Does this model have a high level description and some example code?

swcrazyfan

Owner Oct 3, 2022

Sorry, I don’t have any examples. This model can be used in place of any gpt neo model. It was made as an experiment to make English teaching blogs and articles using gpt neo. I made it public so people can experiment if they’d like.

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